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Your search keyword '"Cremer, Olaf L."' showing total 21 results
Start Over Author "Cremer, Olaf L." Journal critical care
21 results on '"Cremer, Olaf L."'

5. Predictors for extubation failure in COVID-19 patients using a machine learning approach

Author

Fleuren, Lucas M., Dam, Tariq A., Tonutti, Michele, de Bruin, Daan P., Lalisang, Robbert C. A., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco, Kamps, Marlijn J. A., Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Achterberg, Sefanja, Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert B., Cornet, Alexander D., van den Tempel, Walter, Boelens, Age D., Koetsier, Peter, Lens, Judith, Faber, Harald J., Karakus, A., Entjes, Robert, de Jong, Paul, Rettig, Thijs C. D., Arbous, Sesmu, Vonk, Sebastiaan J. J., Fornasa, Mattia, Machado, Tomas, Houwert, Taco, Hovenkamp, Hidde, Noorduijn Londono, Roberto, Quintarelli, Davide, Scholtemeijer, Martijn G., de Beer, Aletta A., Cinà, Giovanni, Kantorik, Adam, de Ruijter, Tom, Herter, Willem E., Beudel, Martijn, Girbes, Armand R. J., Hoogendoorn, Mark, Thoral, Patrick J., and Elbers, Paul W. G.

Published
2021
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6. The Dutch Data Warehouse, a multicenter and full-admission electronic health records database for critically ill COVID-19 patients

Author

Fleuren, Lucas M., Dam, Tariq A., Tonutti, Michele, de Bruin, Daan P., Lalisang, Robbert C. A., Gommers, Diederik, Cremer, Olaf L., Bosman, Rob J., Rigter, Sander, Wils, Evert-Jan, Frenzel, Tim, Dongelmans, Dave A., de Jong, Remko, Peters, Marco, Kamps, Marlijn J. A., Ramnarain, Dharmanand, Nowitzky, Ralph, Nooteboom, Fleur G. C. A., de Ruijter, Wouter, Urlings-Strop, Louise C., Smit, Ellen G. M., Mehagnoul-Schipper, D. Jannet, Dormans, Tom, de Jager, Cornelis P. C., Hendriks, Stefaan H. A., Achterberg, Sefanja, Oostdijk, Evelien, Reidinga, Auke C., Festen-Spanjer, Barbara, Brunnekreef, Gert B., Cornet, Alexander D., van den Tempel, Walter, Boelens, Age D., Koetsier, Peter, Lens, Judith, Faber, Harald J., Karakus, A., Entjes, Robert, de Jong, Paul, Rettig, Thijs C. D., Arbous, Sesmu, Vonk, Sebastiaan J. J., Fornasa, Mattia, Machado, Tomas, Houwert, Taco, Hovenkamp, Hidde, Noorduijn-Londono, Roberto, Quintarelli, Davide, Scholtemeijer, Martijn G., de Beer, Aletta A., Cina, Giovanni, Beudel, Martijn, Herter, Willem E., Girbes, Armand R. J., Hoogendoorn, Mark, Thoral, Patrick J., and Elbers, Paul W. G.

Published
2021
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10. Predicting the clinical trajectory in critically ill patients with sepsis: a cohort study.

Author

Klein Klouwenberg, Peter M. C., Spitoni, Cristian, van der Poll, Tom, Bonten, Marc J., Cremer, Olaf L., on behalf of the MARS consortium, Frencken, Jos F., van de Groep, Kirsten, Koster-Brouwer, Marlies E., Ong, David S. Y., Verboom, Diana, de Beer, Friso M., Bos, Lieuwe D. J., Glas, Gerie J., van Hooijdonk, Roosmarijn T. M., Schouten, Laura R. A., Straat, Marleen, Witteveen, Esther, Wieske, Luuk, and Hoogendijk, Arie J.

Abstract

Background: To develop a mathematical model to estimate daily evolution of disease severity using routinely available parameters in patients admitted to the intensive care unit (ICU).Methods: Over a 3-year period, we prospectively enrolled consecutive adults with sepsis and categorized patients as (1) being at risk for developing (more severe) organ dysfunction, (2) having (potentially still reversible) limited organ failure, or (3) having multiple-organ failure. Daily probabilities for transitions between these disease states, and to death or discharge, during the first 2 weeks in ICU were calculated using a multi-state model that was updated every 2 days using both baseline and time-varying information. The model was validated in independent patients.Results: We studied 1371 sepsis admissions in 1251 patients. Upon presentation, 53 (4%) were classed at risk, 1151 (84%) had limited organ failure, and 167 (12%) had multiple-organ failure. Among patients with limited organ failure, 197 (17%) evolved to multiple-organ failure or died and 809 (70%) improved or were discharged alive within 14 days. Among patients with multiple-organ failure, 67 (40%) died and 91 (54%) improved or were discharged. Treatment response could be predicted with reasonable accuracy (c-statistic ranging from 0.55 to 0.81 for individual disease states, and 0.67 overall). Model performance in the validation cohort was similar.Conclusions: This prediction model that estimates daily evolution of disease severity during sepsis may eventually support clinicians in making better informed treatment decisions and could be used to evaluate prognostic biomarkers or perform in silico modeling of novel sepsis therapies during trial design.Clinical Trial Registration: ClinicalTrials.gov NCT01905033. [ABSTRACT FROM AUTHOR]

Published
2019
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11. Risk factors, host response and outcome of hypothermic sepsis

Author

Wiewel, Maryse A., primary, Harmon, Matthew B., additional, van Vught, Lonneke A., additional, Scicluna, Brendon P., additional, Hoogendijk, Arie J., additional, Horn, Janneke, additional, Zwinderman, Aeilko H., additional, Cremer, Olaf L., additional, Bonten, Marc J., additional, Schultz, Marcus J., additional, van der Poll, Tom, additional, Juffermans, Nicole P., additional, and Wiersinga, W. Joost, additional

Published
2016
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12. Association of diabetes and diabetes treatment with the host response in critically ill sepsis patients

Author

van Vught, Lonneke A., primary, Scicluna, Brendon P., additional, Hoogendijk, Arie J., additional, Wiewel, Maryse A., additional, Klein Klouwenberg, Peter M. C., additional, Cremer, Olaf L., additional, Horn, Janneke, additional, Nürnberg, Peter, additional, Bonten, Marc M. J., additional, Schultz, Marcus J., additional, and van der Poll, Tom, additional

Published
2016
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19. Plasma fractalkine is a sustained marker of disease severity and outcome in sepsis patients.

Author

Hoogendijk, Arie J., Wiewel, Maryse A., van Vught, Lonneke A., Scicluna, Brendon P., Belkasim-Bohoudi, Hakima, Horn, Janneke, Zwinderman, Aeilko H., Klein Klouwenberg, Peter M. C., Cremer, Olaf L., Bonten, Marc J., Schultz, Marcus J., der Poll, Tom van, van der Poll, Tom, and MARS consortium

Subjects
CYTOKINES, INTENSIVE care units, HEALTH outcome assessment, PROGNOSIS, SEPSIS, SEVERITY of illness index, DIAGNOSIS
Abstract

Introduction: Fractalkine is a chemokine implicated as a mediator in a variety of inflammatory conditions. Knowledge of fractalkine release in patients presenting with infection to the Intensive Care Unit (ICU) is highly limited. The primary objective of this study was to establish whether plasma fractalkine levels are elevated in sepsis and associate with outcome. The secondary objective was to determine whether fractalkine can assist in the diagnosis of infection upon ICU admission.Methods: Fractalkine was measured in 1103 consecutive sepsis patients (including 271 patients with community-acquired pneumonia (CAP)) upon ICU admission and at days 2 and 4 thereafter; in 73 ICU patients treated for suspected CAP in whom this diagnosis was refuted in retrospect; and in 5 healthy humans intravenously injected with endotoxin.Results: Compared to healthy volunteers, sepsis patients had strongly elevated fractalkine levels. Fractalkine levels increased with the number of organs failing, were higher in patients presenting with shock, but did not vary by site of infection. Non-survivors had sustained elevated fractalkine levels when compared to survivors. Fractalkine was equally elevated in CAP patients and patients treated for CAP but in whom the diagnosis was retrospectively refuted. Fractalkine release induced by intravenous endotoxin followed highly similar kinetics as the endothelial cell marker E-selectin.Conclusions: Plasma fractalkine is an endothelial cell derived biomarker that, while not specific for infection, correlates with disease severity in sepsis patients admitted to the ICU. [ABSTRACT FROM AUTHOR]

Published
2015
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21. Correction to: Predicting the clinical trajectory in critically ill patients with sepsis: a cohort study.

Author

Klein Klouwenberg, Peter M. C., Spitoni, Cristian, van der Poll, Tom, Bonten, Marc J., Cremer, Olaf L., on behalf of the MARS consortium, Schultz, Marcus J., Horn, Janneke, Scicluna, Brendon, Wiewel, Maryse A., Frencken, Jos F., Groep, Kirsten van de, Koster-Brouwer, Marlies E., Ong, David S.Y., Verboom, Diana, de Beer, Friso M., Bos, Lieuwe D. J., Glas, Gerie J., van Hooijdonk, Roosmarijn T. M., and Schouten, Laura R. A.

Abstract

In the publication of this article [1], there are 4 collaborating authors missing from the 'MARS consortium'. This has now been included in this correction article. [ABSTRACT FROM AUTHOR]

Published
2020
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